The invention relates to a system and method for managing and viewing historical data including security analysts"" predictions (e.g., earnings estimates and buy/sell recommendations) and actual reported data; for measuring, analyzing, and tracking the historical performance of security analysts"" predictions; and creating, managing, backtesting, and using models that use such historical and performance data, attributes and other information to automatically produce better predictors of future events (e.g., corporate earnings or stock-price performance).
Many individuals and institutions analyze financial data, financial instruments, such as equity and fixed-income securities and other things, at least in part to predict future economic events. Such individuals may include, for example, security analysts. The role of the security analyst is generally well-known and includes, among other things, issuing earnings estimates for securities, other financial estimates concerning future economic events (e.g., revenue), recommendations on whether investors should buy, sell, or hold financial instruments, such as equity securities, and other predictions. Security analyst estimates may include, but are not limited to, quarterly and annual earnings estimates for companies whether or not they are traded on a public securities exchange.
Security analysts generally predict a stock""s quarterly or annual earnings well in advance of the time the actual earnings are announced, and from time to time, update their predictions. These predictions are recorded, for example, in the Institutional Brokers Estimates Service (xe2x80x9cIBESxe2x80x9d) database and other commercial databases. The IBES Detail History is complete in its record of estimates and actuals, but limited in its summaries and reports. While IBES provides a summary history database with sunimary-level information per security per fiscal period, it does not provide daily summaries.
Many investors use the simple average of analysts"" estimates, often referred to as the xe2x80x9cconsensus,xe2x80x9d to predict a stock""s earnings, and to make investment decisions based on the consensus earnings estimate. However, this consensus is a naxc3xafve average created by placing equal weight on each analyst""s estimate, regardless of whether the estimate was created recently or months ago, regardless of whether the analyst is a seasoned veteran with a great track record or a rookie, regardless of any historical bias, and regardless of other factors that may be relevant.
Usually more than one analyst follows a given security. Analysts often disagree on earnings estimates and recommendations and, as a result, analysts"" earnings estimates and recommendations often vary.
A number of financial information services providers (xe2x80x9cFISPsxe2x80x9d) gather and- report analysts"" earnings estimates and recommendations. At least some FISPs report the high, low, and mean (or consensus) earnings estimates, as well as mean recommendations for equity securities (as translated to a FISP""s particular scale, for example, one to five). In addition, FISPs may also provide information on what the earnings estimates and recommendations were seven and thirty days prior to the most current consensus, as well as the differences between the consensus for a single equity security and that of the relevant industry. Moreover, for some clients, FISPs provide earnings estimates and recommendations on an analyst-by-analyst basis. An advantage of the availability of analyst-level estimates and recommendations is that a client may view the components of the mean estimate or recommendation by analyst. Various drawbacks exist, however, with these approaches and other known techniques.
For example, prior approaches include a software program that displays all current estimates. For a particular fiscal period, for a particular security, the software provides the ability to simply xe2x80x9cincludexe2x80x9d or xe2x80x9cexcludexe2x80x9d each estimate or recommendation from the mean. This is problematic for several reasons. First, commercially available databases of estimates and recommendations contain xe2x80x9ccurrentxe2x80x9d data on thousands of stocks. Each stock may have estimates from 1 to 70 or more analysts. In addition, each analyst may provide estimates for one or more periods. The data may be updated throughout the day. Manually dealing with this volume of information may be time consuming and tedious.
A second drawback is that with current techniques, if an individual were inclined to determine which estimates (or recommendations) should get more weight, and which estimates should get less or no weight, the large volume of analysts makes it extremely difficult to determine which analysts provide more useful information than others. Current techniques lack sufficient ability to intelligently measure historical analyst performance and beneficially use such measurements.
A third drawback is that while it is possible to imagine various weighting systems or algorithms, it is difficult to effectively implement or test them. Current systems do not provide the ability to effectively devise new estimate (or recommendation) weighting algorithms; nor do they provide the ability to easily test a historical performance.
A fourth drawback with current techniques is that there are limited tools for easily and effectively analyzing historical estimates and recommendations. While the data is available, often times unique code is written to conduct a specific analysis. Changing the analysis often requires rewriting code.
These and other drawbacks exist with existing systems.
An object of the invention is to overcome these and other drawbacks with existing systems and methods.
Another object of the invention is to provide an improved computer implemented system and methods for use with a database of historical data relating to security analyst earnings estimate or other predictions.
Another object of the invention is to include within such a system and methods, a history view module to enable users to view the historical data for a given security either: i) as a time series of earnings estimates and revisions for each analyst selected, for a selected period of time, for a selected earnings event; or ii) in a xe2x80x9csnapshotxe2x80x9d view with calculated metrics as of a given date.
Another object of the invention is to provide a computer implemented system and methods to enable a user to custom define a model that can be applied to current estimates from a plurality of selected sources to generate an enhanced composite estimate, and to enable a user to manage, backtest and view results of such models.
Another object of the invention is to provide a computer implemented system and methods that enable a user to view, measure and analyze the past performance for a particular contributor (e.g., a broker, an analyst or a broker/analyst pair), or for a given security the various contributors that have qualifying estimates. Other views may also be available.
These and other objects of the invention are accomplished according to various embodiments and aspects of the invention, as described below. The various features and functions of the invention may be used alone or in combination to form a system and method for managing, viewing and analyzing historical security analyst data, and generating enhanced composite estimates to better predict future earnings, stock-price performance, or other events.
According to one embodiment, the invention uses a modular design, including one or more of the following modules: Contributors, Stocks, Models, History, and Performance. Other modules may also be used. Under the Contributors module, the user may select an analyst, broker, security, and other categories and view relationships therebetween. Under the Stocks module, the user may define stock filters and group stocks into stock sets. The stock sets may be used, for example, to facilitate testing and use of user-defined models, and for other purposes. Under the Models module, the user may create, manage and edit models, backtest the models against the historical database, view results of the backtest and perform other functions. Under the History module, historical estimate and actual data may be viewed in chart or in grid format. For example, a chart view may display estimates and actual data graphically and allow for visually backtesting models and analyst performance. The snapshot view displays detailed data in tabular format for a selected xe2x80x9cAs Of Date.xe2x80x9d Other historical data and formats may also be used. Under the Performance module, the user may create and display metrics for analyzing analyst performance, analyst and/or broker accuracy reports, aggregated by analyst, broker, ticker, any combination thereof, or in other aggregations. In each of the above identified modules, other options may be available to the user.
According to one aspect of the invention, a software tool and methods are provided (e.g., a graphical user interface (GUI)) to enable a user to easily view historical data relating to earnings estimates (and other information) from a plurality of sources (e.g., analysts). The historical data is stored in a database and is commercially available from one or more vendors such as First Call, IBES, etc. The invention also calculates and selectively displays daily summary-level statistics such as Calculated Low, Calculated Mean, Calculated High, and Number of Analysts. The software tool preferably includes a graphical user interface that enables the historical data to be presented in the form of a chart, a graph, or other format.
The graphical view preferably comprises a time series view (e.g., estimate values on the y-axis, time on the x-axis) of each or selected analyst""s estimates and revisions for a selected security, and earnings event over a selected period. Other information may be simultaneously displayed, such as actual reported earnings.
Sources of estimates (or other predictions) may include analysts, brokers, analyst broker pairs and other sources. The software may also treat the high estimate, low estimate, consensus estimate, enhanced composite estimates (detailed below) and other calculated or derived values as sources, and enable a user to selectively show each as a time series display. Preferably, a user control portion of the GUI enables a user to selectively cause the display to show or hide the time series for any one or more or all sources, by selecting and deselecting individual sources, or through a select all or deselect all feature. Other features and options may also be available to the user. Through the display, the user may simultaneously view a time series of earnings estimates and revisions for one or more selected sources for a selected security, for a selected earnings events.
According to another aspect of the invention, a stock price time series may be juxtaposed with or overlaid on the selected sources time series. This is particularly useful to see if there is a correlation between one or more analysts"" estimates or revisions thereto, and stock price movement.
Another feature of the display is a user selected xe2x80x9cAs-of Datexe2x80x9d which may be displayed as a vertical bar, for example. The user may view historical data as of a user selected date and simultaneously display summary estimate data and other information as of that date. Summary estimate data may comprise, for example, data derived from a distribution of estimates and enhanced composite estimates. The user may select the snapshot view to view detailed information for each activated analyst as of the selected date.
Another aspect of the invention enables individuals to create models that give more weight to analyst predictions that are more likely to be accurate and less weight to those less likely to be accurate. When the models are applied to current estimates, the present invention produces earning estimates that may more accurately predict earnings than a consensus estimate (or other estimate), depending on the accuracy of the model created. The present invention enables the user to develop, test and refine models by comparing the estimates of the models with the historical estimate data.
According to another embodiment of the present invention, a Model module enables users to create, backtest, and manage a model. Other functions are also available. The model may comprise user defined rules that are applied to selected data for a plurality of contributors to create an enhanced composite prediction. The user may specify certain rules or factors by which to exclude one or more data items, contributors, or other criteria. In addition, the user may assign weights to various factors involved in contributors"" predictions to obtain an enhanced composite.
A user may create a model by identifying various factors to be taken into account in the model. For each factor, a user specifies rules by which each non-excluded analyst is assigned an N-score (normalized) according to the rules. Such factors may include, for example, accuracy, All Star (or other) rating, broker list, experience, estimate age, and other factors. Each factor is assigned a weight to enable a user to place greater emphasis on one or more factors for a given model. For each model, the analyst""s N-score for each factor is multiplied by the factor weight and those weighted N-scores are summed for each analyst. The actual emphasis placed on an analyst""s current estimate is determined by taking the sum of the analyst""s weighted factor scores divided by the sum of the weighted factor scores for all analysts.
The user may specify certain exclusion factors. For example, exclusion factors may include excluding estimates that are older than a particular number of days and estimates that are more than a user specified number of standard deviations from the mean. In addition, an exclusion may be specified for estimates older than a user-specified amount of time before or after a company""s last earnings report date. Exclusion factors can exclude an entire group or class of estimates from being considered, such as all estimates that are older than 100 days.
The present invention enables the user to view, in a single display screen, current analyst data commingled with analyst performance data and attributes, values and elements of models on an analyst-by-analyst basis. For example, the snapshot view details analyst estimate data, such as the current estimate, the current estimate date, the age of the estimate in days, the previous estimate, the date of the previous estimate, the change between the two most recent estimate, and other data. The user may readily compare the current analyst data for each analyst for a given stock and simultaneously view values and elements that comprise a selected model, such as factors, N-scores, exclusions, weights, and other elements.
Through these and other tools, the user may intelligently develop models that more accurately predict estimates by viewing and analyzing the components of a model. For example, a user may determine where particular groupings of estimate revisions (e.g., a cluster) exist and more intelligently create accurate models taking clusters into account. The present invention enables a user to easily compare actual current estimates with enhanced composite estimates that are a result of a model. Various algorithms for comparing these values may be used and various alerts may be issued when the difference satisfies user specified criteria.
The present invention enables the user to view a model as a xe2x80x9cclear boxxe2x80x9d, as opposed to a xe2x80x9cblack boxxe2x80x9d. In other words, the user may easily view factors, N-scores, factor weights and other information that comprise a model. For example, by viewing the specific weights and N-scores, along with other information, the user may readily determine why an enhanced composite deviates from a consensus estimate. Specific detailed numerical values relating to analysts performance and attributes are also provided to the user for comparing, sorting, and ranking. Through the snapshot view, the user may view detailed analyst estimate data, including historical and current data, that informs the user what factors, weights, and N-scores comprise a model. The ability to analyze models on a detailed level enables the user to identify important factors, values, and trends to develop more accurate models.
Another aspect of the invention includes a Performance module to further assist the user in developing more accurate models. The Performance module also enables the user to measure and compare analysts"" performance, in absolute terms and relative to other analysts, sources or other data in estimating stock earnings. This feature is useful for determining how well analysts in a particular brokerage are doing, or which analyst has the best performance for a particular ticker. For example, information regarding a particular stock and multiple contributors; one particular contributor and multiple stocks; and a unique contributor-stock pair may be displayed. This enables a business model that provides the ability to rank analysts based on user-selected objective criteria.
In displaying a particular stock and multiple contributors, each contributor who made an estimate in the selected fiscal period or periods for a selected security may be displayed. Summary performance metrics; aggregate performance metrics; and other information may be displayed for each contributor. Further, a portion of the display may display period-by-period performance for a selected security for each period in the selected fiscal periods. The user may also elect to filter the displayed list of contributors who made an estimate in the selected fiscal period or periods to those contributors who have a current estimate, so that either all contributors, only current contributors or some other group may be shown.
In displaying a particular contributor and multiple stocks, each security for which that contributor has made an estimate for a selected contributor, in a selected fiscal year may be shown. Further, aggregate performance metrics may be displayed for the selected contributor and each displayed security. The aggregate performance metrics may be displayed for a selected time frame and aggregated over each period in the selected period. In addition, a portion of the display may display period-by-period performance for the selected contributor, for one or more securities for each period in the selected fiscal periods.
In displaying a unique contributor-security pair, the user may select a contributor-security pair where period-by-period performance metrics for each period in the selected fiscal periods may be shown.
The present invention provides a graphical environment for quantitative researchers and other entities, to create, investigate, backtest and apply models to create more valuable estimates. Individuals, such as portfolio managers, may easily apply these models to assist with stock selection strategies and measure the performance of analysts. The present invention also provides research departments, for example, regular and objective reports on the performance of individual analysts compared to other analysts following the same stocks (or other benchmarks), as well as the performance of the research department as a whole. Individual investors may also receive information generated by models (e.g., enhanced composite estimates) through a web-site implementation of the present invention, through internet finance portals, and other portals. Additionally, subscribers may receive information alerts, e.g., when an enhanced composite estimate changes when it differs from the consensus estimate by certain user specified or other criteria or at other times. Various other business methods may be implemented using the technology described herein.